Semiconductor devices may be fabricated on the surface of a semiconductor wafer in layers and later cut into individual chips. The individual chips thus fabricated are subjected to a series of tests to determine if the chips function properly both before and after being cut. These tests are sometimes repeated at several points in the manufacturing process, since the steps involved in cutting and packaging the chips can result in thermal and mechanical stresses which can induce failures of individual chips. The tests are designed to identify parts that are actually failing when tested, a failure sometimes referred to as a “time-zero” failure.
But many failures that occur in semiconductor chips are not “time-zero” failures, but failures that occur later after the chips have been in operation for a short time. These failures, sometimes referred to as “infant-mortality” or “early” failures, are sometimes identified through the use of a “burn-in” process, in which the chips are operated for an extended period (compared to the duration of normal production testing) beyond the electrical and environmental ranges defined by the design engineers for normal operation. This operational test period may identify a significant number of failures, but this is accomplished at the expense of the additional cost of testing, as well as a reduced life expectancy of the chips tested.
Some manufacturers have used a “no burn-in” approach, using time-zero failures to predict early failures without a production burn-in. Using time-zero failures to predict marginal chips, however, does not always predict failures of chips that are defective. These unpredicted “statistical outliers” tend to increase in number as the dimensions of the semiconductor structures within the chips decrease, and are thus not reliably predicted by time-zero-based no burn-in techniques when applied to many of today's sub-micron semiconductor devices.
Analysis of devices that have actually failed can provide an improved statistical basis for identifying statistical outliers, as illustrated by the methods described in U.S. Pat. No. 7,129,735, issued on Oct. 31, 2006 and entitled “Method For Test Data-Driven Statistical Detection of Outlier Semiconductor Devices,” which is herein incorporated by reference. But as production techniques and yields have improved, the number of failed devices has decreased, providing a progressively smaller sample size from which to extract failure data. Manufacturers have also increased the use of “stop on fail” testing (wherein testing of a device is stopped upon the occurrence of any failure) in order to decrease the overall testing time (and the associated cost of testing) of the devices. These factors result in a scarcity of failure data, which produces a decrease in the statistical confidence of the results of failure predictions based on the failure data, thus decreasing the reliability of the resulting failure predictions.